RAPIDSNPs: A new computational pipeline for rapidly identifying key genetic variants reveals previously unidentified SNPs that are significantly associated with individual platelet responses

CRISPR-edited megakaryocytes for rapid screening of platelet gene functions

Human anucleate platelets cannot be directly modified using traditional genetic approaches. Instead, studies of platelet gene function depend on alternative models. Megakaryocytes (the nucleated precursor to platelets) are the nearest cell to platelets in origin, structure, and function. However, achieving consistent genetic modifications in primary megakaryocytes has been challenging, and the functional effects of induced gene deletions on human megakaryocytes for even well-characterized platelet genes (eg, ITGA2B) are unknown. Here we present a rapid and systematic approach to screen genes for platelet functions in CD34+ cell-derived megakaryocytes called CRIMSON (CRISPR-edited megakaryocytes for rapid screening of platelet gene functions). By using CRISPR/Cas9, we achieved efficient nonviral gene editing of a panel of platelet genes in megakaryocytes without compromising megakaryopoiesis. Gene editing induced loss of protein in up to 95% of cells for platelet function genes GP6, RASGRP2, and ITGA2B; for the immune receptor component B2M; and for COMMD7, which was previously associated with cardiovascular disease and platelet function. Gene deletions affected several select responses to platelet agonists in megakaryocytes in a manner largely consistent with those expected for platelets. Deletion of B2M did not significantly affect platelet-like responses, whereas deletion of ITGA2B abolished agonist-induced integrin activation and spreading on fibrinogen without affecting the translocation of P-selectin. Deletion of GP6 abrogated responses to collagen receptor agonists but not thrombin. Deletion of RASGRP2 impaired functional responses to adenosine 5'-diphosphate (ADP), thrombin, and collagen receptor agonists. Deletion of COMMD7 significantly impaired multiple responses to platelet agonists. Together, our data recommend CRIMSON for rapid evaluation of platelet gene phenotype associations.

Sensitivity analysis based on the random forest machine learning algorithm identifies candidate genes for regulation of innate and adaptive immune response of chicken

Two categories of immune responses—innate and adaptive immunity—have both polygenic backgrounds and a significant environmental component. The goal of the reported study was to define candidate genes and mutations for the immune traits of interest in chickens using machine learning–based sensitivity analysis for single-nucleotide polymorphisms (SNPs) located in candidate genes defined in quantitative trait loci regions. Here the adaptive immunity is represented by the specific antibody response toward keyhole limpet hemocyanin (KLH), whereas the innate immunity was represented by natural antibodies toward lipopolysaccharide (LPS) and lipoteichoic acid (LTA). The analysis consisted of 3 basic steps: an identification of candidate SNPs via feature selection, an optimisation of the feature set using recursive feature elimination, and finally a gene-level sensitivity analysis for final selection of models. The predictive model based on 5 genes (MAPK8IP3 CRLF3, UNC13D, ILR9, and PRCKB) explains 14.9% of variance for KLH adaptive response. The models obtained for LTA and LPS use more genes and have lower predictive power, explaining respectively 7.8 and 4.5% of total variance. In comparison, the linear models built on genes identified by a standard statistical analysis explain 1.5, 0.5, and 0.3% of variance for KLH, LTA, and LPS response, respectively. The present study shows that machine learning methods applied to systems with a complex interaction network can discover phenotype-genotype associations with much higher sensitivity than traditional statistical models. It adds contribution to evidence suggesting a role of MAPK8IP3 in the adaptive immune response. It also indicates that CRLF3 is involved in this process as well. Both findings need additional verification.

Functional Genomics for the Identification of Modulators of Platelet-Dependent Thrombus Formation

Despite the absence of the genome in platelets, transcription profiling provides important insights into platelet function and can help clarify abnormalities in platelet disorders. The Bloodomics Consortium performed whole-genome expression analysis comparing in vitro–differentiated megakaryocytes (MKs) with in vitro–differentiated erythroblasts and different blood cell types. This allowed the identification of genes with upregulated expression in MKs compared with all other cell lineages, among the receptors BAMBI, LRRC32, ESAM, and DCBLD2. In a later correlative analysis of genome-wide platelet RNA expression with interindividual human platelet reactivity, LLRFIP and COMMD7 were additionally identified. A functional genomics approach using morpholino-based silencing in zebrafish identified various roles for all of these selected genes in thrombus formation. In this review, we summarize the role of the six identified genes in zebrafish and discuss how they correlate with subsequently performed mouse experiments.